Functional near-infrared spectroscopy-based prefrontal cortex oxygenation during working memory tasks in sickle cell disease

Abstract. Significance Sickle cell disease (SCD), characterized by painful vaso-occlusive crises, is associated with cognitive decline. However, objective quantification of cognitive decline in SCD remains a challenge, and the associated hemodynamics are unknown. Aim To address this, we utilized functional near-infrared spectroscopy (fNIRS) to measure prefrontal cortex (PFC) oxygenation responses to N-back working memory tasks in SCD patients and compared them with healthy controls. Approach We quantified the PFC oxygenation rate as an index of cognitive activity in each group and compared them. In half of the participants, a Stroop test was administered before they started N-back to elevate their baseline stress level. Results In SCD compared to healthy controls, we found that (1) under a high baseline stress level, there were significantly greater oxygenation responses during the 2-back task, further elevated with histories of stroke; (2) there was a marginally slower N-back response time, and it was even slower with a history of stroke; and (3) the task accuracy was not different. Conclusions Additional requirements for processing time, PFC resources, and PFC oxygenation in SCD patients offer an important basis for understanding their cognitive decline and highlight the potential of fNIRS for evaluating cognitive functions.


Model-based filtering improved brain component in fNIRS: Finger PPGa served as a surrogate measure of skin blood flow changes and ETCO2 to represent breathing-induced cerebral blood flow changes.
The PPGa and ETCO2 were used as inputs to the proposed dynamic systems model, providing two advantages.First, any discrepancy between measured finger blood flow and actual scalp blood (but not measured) would be mitigated by the impulse response function found by fitting the model.Second, using physiological measurements helped avoid making blind assumptions that other methods like PCA and ICA are based on.Finger PPGa was a reasonable surrogate of scalp blood flow, and ETCO2 which reflected CO2 concentration in the brain has been reported as a critical confounder in fNIRS signal 35,47 .We also found a reasonable resemblance between the fingertip PPGa and the scalp PPGa on the forehead measured by another NIRS device equipped with a short separation (~5 mm; correlation coefficient >.5, Figure S2), supporting the use of fingertip PPGa as a surrogate measure of scalp blood flow influencing fNIRS measurement.There was an indication of hyperactivation to 2-back in SCD in quad 3 (P=.017,before correcting for multiple comparisons), while there seen an elevated 0-back response in controls in general and strongest at quad 2 (P=.016).Age and sex did not show significance nor interaction with other variables (Page=.7,Psex=.9).Furthermore, N-back difficulties with the * label denoted where we found statistically significantly greater oxygenation response in SCD when they were normalized by average 0-back response of each channel (P=.008, .003;.009,.004,respectively from quad2:1-back, 2-back; quad3:1-back and 2-back; Not shown).

Possible differences between overt vs. silent stroke in SCD
The comparison between the overt and silent stroke in their PFC oxygenation showed significantly suppressed trends in the silent stroke SCD group compared with the overt stroke SCD group.This separation becomes even stronger when the hemoglobin count was taken into account (Not shown).There may be important/significant differences between the stroke types being overt vs silent; however, we did not analyze further, due to the limited sample size.In this section, for reference, the comparisons of all four groups are attached, where the four groups were the control (N=18), SCDn (no stroke; 15), SCDhso (Overt stroke; 3), and SCDhss (Silent stroke; 5) groups.Preliminary comparisons showed relatively lower accuracy rate in the SCDhss group, increased PFC oxygenation rate in SCD during N-back tasks in general, except in the SCDhss group, and longer response times in SCDhss than other groups.Motion artifact detection based on the sliding window signal variation method, followed by spline and wavelet transformation filtering, removed both step and spike types of signal artifacts and improved the quality of the fNIRS data.

Figure
Figure S1.N-back increased brain oxygenation while possible decrease in signal amplitude due to skin vasoconstriction and hyperventilation.The signal contamination due to skin vasoconstriction and hyperventilation was estimated and subtracted from the original fNIRS HbO signal using model-based filtering.

Figure S2 .
Figure S2.Scalp vs finger blood flow comparison via fNIRS, pulse ox (PPGa), and laser Doppler flowmetry showed more similar in signal waveform between the PPGa and short-separation fNIRS channel.The shortseparation NIRS device was not available during the period of active enrollment.

Figure S3 .
Figure S3.Oxygenation to N-back in SCD vs healthy controls indicated a difference.There was an indication of hyperactivation to 2-back in SCD in quad 3 (P=.017,before correcting for multiple comparisons), while there seen an elevated 0-back response in controls in general and strongest at quad 2 (P=.016).Age and sex did not show significance nor interaction with other variables (Page=.7,Psex=.9).Furthermore, N-back difficulties with the * label denoted where we found statistically significantly greater oxygenation response in SCD when they were normalized by average 0-back response of each channel (P=.008, .003;.009,.004,respectively from quad2:1-back, 2-back; quad3:1-back and 2-back; Not shown).

Figure S4 .
Figure S4.Possible significant differences in response time and PFC oxygenation between SCD with the histories of overt stroke vs silent stroke.Response times seemed the longest in SCD with the histories of silent stroke compared to other groups (center), while there was no clear evidence of differences in task accuracy (left).The grand average of the PFC oxygenation responses showed hyper-activation in the SCD groups, but not in SCD with the histories of silent stroke as it showed a flat response to N-back.

Figure S5 .
Figure S5.An fNIRS signal cleaning example of ~15 minutes excerpt: Top row, showing step and spike type signal artifacts (blue line), identified as 0 in the dark orange line, corrected by spline method shown in light orange.Bottom row shows the effect of the following wavelet filtering applied to the HbO-Spline signal, providing additional cleaning for the residual spikes.